Conversational Task Assistants (CTAs) guide users in performing a multitude of activities, such as making recipes. However, ensuring that interactions remain engaging, interesting, and enjoyable for CTA users is not trivial, especially for time-consuming or challenging tasks. Grounded in psychological theories of human interest, we propose to engage users with contextual and interesting statements or facts during interactions with a multi-modal CTA, to reduce fatigue and task abandonment before a task is complete. To operationalize this idea, we train a high-performing classifier (82% F1-score) to automatically identify relevant and interesting facts for users. We use it to create an annotated dataset of task-specific interesting facts for the domain of cooking. Finally, we design and validate a dialogue policy to incorporate the identified relevant and interesting facts into a conversation, to improve user engagement and task completion. Live testing on a leading multi-modal voice assistant shows that 66% of the presented facts were received positively, leading to a 40% gain in the user satisfaction rating, and a 37% increase in conversation length. These findings emphasize that strategically incorporating interesting facts into the CTA experience can promote real-world user participation for guided task interactions.

翻译：对话任务助手（CTA）引导用户执行多种活动，例如制作食谱。然而，确保用户与CTA的交互保持吸引力、趣味性和愉悦性并非易事，尤其是对于耗时或具有挑战性的任务。基于人类兴趣的心理学理论，我们提出在与多模态CTA交互过程中，通过语境化且有趣的陈述或事实来吸引用户，以减轻疲劳和任务完成前的放弃行为。为实现这一想法，我们训练了一个高性能分类器（F1分数82%），以自动识别与用户相关且有趣的事实。我们利用该分类器创建了一个针对烹饪领域的特定任务有趣事实标注数据集。最后，我们设计并验证了一种对话策略，将识别出的相关有趣事实融入对话中，以提升用户参与度和任务完成率。在主流多模态语音助手的实际测试中，66%展示的事实获得积极反馈，用户满意度评分提升40%，对话长度增加37%。这些发现强调，将有趣事实策略性地融入CTA体验中，能够有效促进实际场景下引导式任务交互中的用户参与。